CASPIAN SEA LEVEL PREDICTION USING ARTIFICIAL NEURAL NETWORK AND EMPIRICAL MODE DECOMPOSITION
This paper demonstrates the possibility of using nonlinear modeling for prediction of the Caspian Sea level. Phase space geometry of the of a model can be reconstructed by the embedology methods. Dynamical invariants, such as the Lyapunov exponents, the Kaplan-Yorke dimension, and the prediction hor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Lomonosov Moscow State University
2010-12-01
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| Series: | Geography, Environment, Sustainability |
| Subjects: | |
| Online Access: | https://ges.rgo.ru/jour/article/view/235 |